Polar codes proposed by E. Arikan “Channel polarization: A method for constructing capacity achieving codes for symmetric binary-input memoryless channels” (IEEE Transactions On Information Theory, Volume 55, No. 7, pages 3051-3073, July 2009 (REF 1)) represent a first class of correcting codes that achieve the bandwidth of a broad class of communications channels. Polar codes are linear block codes generated by a submatrix of matrix A=BmR⊗m=R⊗mBm where Bm is a bit-organized permutation matrix
      R    =          (                                    1                                0                                                1                                1                              )        ,and ⊗m is m-fold Kronecker product of the matrix by itself. Thus, the code word of the polar code is c=uA, c∈GF(2)n, n=2m, where ui, i∈(0, 1, . . . , n−1)/F are coded information symbols, and ui, i∈F are assumed to be 0 (frozen symbols, such as symbols whose values never change). Classic method of decoding y obtained by transmission of c over a memory-free channel, symmetric by output, is the successive cancellation method (SC). The method comprises successively finding the most probable a posteriori values ui using values u0, . . . , ui−1, y0, . . . , yn−1. The found value ui is used in the subsequent steps of the decoding algorithm. It can be shown that the combination of a linear transformation specified by matrix A, physical data channel and SC decoder (assuming that intermediate solutions are correct) are represented as a set of n bit subchannels of various quality, such as each ui is assumed to be transmitted over i-th subchannel. A quality (such as bandwidth, probability of error per bit) of these subchannels is analyzed using the probability density evolution method consisting in computing the density of distribution of log likelihood ratios computed at various stages of the SC method (I. Tal and A. Vardy “How to construct polar codes”, IEEE Transactions On Information Theory, Volume 59, No. 10, October 2013 (REF 2)), or its Gaussian approximation (P. Trifonov “Efficient design and decoding of polar codes”, IEEE Transactions on Communications, Volume 60, No. 11, pages 3221-3227, November 2012 (REF 3)). A possible method of constructing a polar code of length n and dimension k is to select F as a plurality of indices of the worst bit subchannels.